In the face of “data everywhere” and with broad access to map data (e.g., via the Internet), users are often faced with a confounding plethora of data when looking at data presented together with maps. Often a map is presented to a user where the map is both overly dense, and overly sparse. Consider a user searching for “waterfront eateries” (e.g., restaurants on the waterfront) in lower Manhattan. In such a case, almost any geographic area selected will at the same time be too dense (e.g., too dense in the vicinity of the waterfront itself), and too sparse (e.g., since there are no restaurants on the waterfront even a one block away from the waterfront).
Merely scaling the map linearly (e.g., via zoom-in or zoom-out) does not ameliorate the problem. Instead, what is needed are techniques for presenting location data using some meaningful scale other than mere geographic distances. And, such presentation needs to support decision-making by the user—specifically by presenting the needed location information, yet without obscuring the important criteria for decision-making.
Legacy systems have provided only rudimentary decision support and in some cases, the aforementioned legacy systems produce a plethora of information—much of which is unimportant to decision-making, and which plethora of information tends to obfuscate the decision-making process.
Some advanced legacy decision support systems have attempted to aid the user by superimposing the location data over an abstracted geographic map. Yet, such abstracted geographic maps, even when using overlay techniques are still deficient in that such techniques do not consider (possibly dispositive) decision criteria other than geography.
Improved techniques are needed to facilitate more flexible decision support, and to aid the user by displaying graphs and other user interface aids based on the decision criteria deemed as important to the user.